An interval formulated to have specific probability of containing the real value of an unknown parameter. A 95 percent confidence interval has a 95 percent probability of containing the parameter being estimated.
An interval around an observed parameter such as relative risk which is guaranteed to include the true value to some level of confidence (usually 95%). That level of confidence is only justified to the extent that bias is absent from the study. A well known election poll advertises itself "this poll is accurate to within 2 percentage points 99% of the time." This is a way of saying, in language aimed at voters (perhaps a skewed sample from the standpoint of IQ) that the 99% CI around the reported percentages is
Because it was not feasible to survey every resident of Vermont, the survey data provide an estimate of the true value of one or more characteristics. The standard error is used to calculate a range that would be expected to contain the true value at least 95% of the time. To compute this range or margin of error, multiply the measure's standard error times 1.96. This product is then added to the point estimate to calculate the high end of the range ( Upper Limit) or subtracted from the point estimate to determine the low end of the range ( Lower Limit). Caution should be exercised in drawing inferences from point estimates within wide ranges. The ranges are represented as line bars in many graphs.
Select confidence level, such as 95%, or turn intervals off. Example confidence interval result - 23.2 (21.2-24.7).
A range around the sample estimate in which the population estimate is expected to fall with a specified degree of confidence, usually 95% of the time or 90% of the time.
the range around a survey result for which there is a defined statistical probability that it contains the true population parameter.
A range of values, with an upper and lower limit, around a school's or district's percentage of proficient students within which there is “confidence” the true percentage lies.
In statistics, confidence intervals are the most prevalent form of interval estimation.